cd1a5446ce793d09f28d021c466a279301eb51f0,deslib/des/meta_des.py,METADES,select,#METADES#,294

Before Change

        -------
        indices : the indices of the selected base classifiers
        
        indices = [idx for idx, _ in enumerate(competences) if competences[idx] > self.gamma]

        // if no classifier was selected, use the whole pool
        if len(indices) == 0:

After Change

        if competences.ndim < 2:
            competences = competences.reshape(1, -1)

        selected_classifiers = (competences > self.selection_threshold)
        // For the rows that are all False (i.e., no base classifier was selected, select all classifiers (all True)
        selected_classifiers[~np.any(selected_classifiers, axis=1), :] = True

        return selected_classifiers

    def estimate_competence(self, query, predictions):

Instances